Internship: Autonomous vehicle path planning and control design and experiments
MERL is seeking a motivated and qualified individual to work with MERL staff on path planning and predictive control for autonomous vehicles. The candidate is expected to design, implement and test the algorithms in a multi-vehicle testbench with car-like robots. The candidate should have solid background in ROS, C++, and numerical algorithms. Previous experience of experimental work with robot testbenches (UGV, UAV, UUV) is highly desired. Background on model predictive control, sampling-based planning methods, and particle filtering is a plus. Publication of the results produced during the internship is anticipated. Duration of the internship is expected to be 3 to 6 months, with potential of extension. Expected start of the position is December 2017-January 2017, but dates are flexible. The position is open to (experienced) Master students, holder of MSc, and PhD students.
Research Area: Mechatronics
Contact: Stefano Di Cairano
Do you have a LinkedIn account? Import your resume and save time!